This study examined the spatial distribution and seasonal fluctuations of population densities of phlebotomine sand flies and was designed to obtain baseline data on the population trends of Phlebotomus argentipes, P. papatasi, and Sergentomyia spp. in a visceral leishmaniasis endemic area of Bihar, India. Beginning on 28 October 2009 and through 20 October 2010, 63 CDC light traps were evenly distributed in human homes, cattle sheds, combined dwellings, chicken coops, and adjacent vegetation areas in three villages in the Saran District of Bihar State. Sand fly collections were made on a weekly basis, sorted, and identified according to species, sex, and feeding status of the two genera. The daily temperatures and relative humidity ranges were collected in a representative human home, cattle shed, and combined dwelling in each of the three study villages. Village census surveys were conducted in the three study villages in February 2010, acquiring human population data, structural composition data, and livestock census information, and documenting the history of visceral leishmaniasis within each household. A total of 52,653 sand flies was trapped and identified over 3,276 trap-nights. Peaks in abundance were observed in November 2009, March and April, June through August. Of the sand flies trapped, 72.1% were P. argentipes, 27.1% Sergentomyia spp., and 0.8% P. papatasi. Distribution of the sand fly captures included 30.6%, 26.7%, 18.6%, 12.1%, and 12.0% from vegetation, combined dwellings, cattle sheds, housing, and poultry houses, respectively. Journal of Vector Ecology 36 (Supplement 1): S106-S117. 2011.
Abundance and other aspects of population ecology have long been known to contribute to shaping the geography of species' distributions. In particular, abundance patterns have recently been shown to negatively correlate with environmental distance from conditions in the center of a species' abiotic niche, rather than vary with distance from the geographic center of a species' distribution. We tested for such associations across 8 species of endangered or threatened bird species in North America using population trend data derived from > 4 decades of North American Breeding Bird Surveys. Although we found no consistent overall pattern, we did observe negative population trends at conditions that were the most extreme within species' niches. This suggests that niche peripherality is a relevant factor to consider in conservation planning. Specifically, environmentally peripheral sites may be poor places in which to protect populations of endangered and threatened species, irrespective of how centrally they may occur within species' geographic distributions.
Detailed spatio‐temporal information about geographic distributions of species is critical for biodiversity analyses in conservation and planning. Traditional correlative modelling approaches use species observational data in model calibration and testing in a time‐averaged framework. This method averages environmental values through time to yield a single environmental value for each location. Although valuable for exploring distributions of species at a broad level, this averaging is one of myriad factors impacting model quality and reliability. We sought to optimize traditional correlative niche model performance in distributional ecology contexts by incorporating time specificity into the existing modelling framework. We modified the existing framework to account for temporal dynamics in species' distributions to produce more robust, temporally explicit models. Using the Wood Thrush Hylostichla mustelina as our study species, we introduce a method of (a) deriving a temporally explicit pseudo‐absence dataset using kernel density estimates to replicate relative sampling of sites through time, and (b) incorporating temporally explicit covariates in model calibration. By accounting for location, and month and year of primary data collection, the time‐specific models successfully yielded dynamic predictions reflecting known distributional shifts in Hylocichla mustelina's annual movement pattern. The modified data preparation steps that we present incorporate temporal dimensions into traditional correlational modelling approaches improving predictive capacity and overall utility of these models for highly mobile, short‐lived or behaviourally complex species. With the ability to estimate species' niches in greater detail, time‐specific models will be able to address specific concerns of species‐level management and policy development for highly mobile and/or migratory species, as well as disease vectors of public health interest.
Species invasions represent a significant dimension of global change yet the dynamics of invasions remain poorly understood and are considered rather unpredictable. We explored interannual dynamics of the invasion process in the Eurasian collared dove () and tested whether the advance of the invasion front of the species in North America relates to centrality (versus peripherality) within its estimated fundamental ecological niche. We used ecological niche modelling approaches to estimate the dimensions of the fundamental ecological niche on the Old World distribution of the species, and then transferred that model to the New World as measures of centrality versus peripherality within the niche for the species. Although our hypothesis was that the invasion front would advance faster over more favourable (i.e. more central) conditions, the reverse was the case: the invasion expanded faster in areas presenting less favourable (i.e. more peripheral) conditions for the species as it advanced across North America. This result offers a first view of a predictive approach to the dynamics of species' invasions, and thereby has relevant implications for the management of invasive species, as such a predictive understanding would allow better anticipation of coming steps and advances in the progress of invasions, important to designing and guiding effective remediation and mitigation efforts.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.